R2platform datascience annals

  Meta cohorts can be very interesting to get a quick comprehensive overview of the gene expression pattern for your gene of interest. Here a meta cohort that has been around for some time, but still provides valuable information at a single glance. The integration of a harmonised Affymetrix cohort of nearly 28.000 bulk profiles. Using the 'sample maps' feature in the free open online R2 platform (  https://r2.amc.nl  ), you can use data driven representations, such as UMAP, tSNE, PCA etc for exploration. Or make use of a wealth of other features available in the versatile data science tool, intended for biomedical researchers.

Genomic data from The Cancer Genome Atlas (TCGA) project has enabled comprehensive molecular profiling of diverse cancer types. The extensive sample size within TCGA provides an invaluable resource for investigating tumor heterogeneity. Effective exploration of this dataset by researchers and clinicians is essential for discovering novel therapeutic and diagnostic biomarkers.  The R2Platform, provides an easy interface to explore the rich resource at different levels. By example, subset the cohort to paired tumor / normal patients only and discover how the expression of your gene of interest changes from normal to tumor. The R2 data science platform for biomedical researchers serves as a robust tool for in silico validation of target genes and the identification of candidate biomarkers for tumor subtype-specific research. The R2 portal has the potential to accelerate cancer research by providing accessible and comprehensive analytical capabilities. R2 is already cited in more than ...

  R2: An Interactive Online Portal for Tumor Subgroup Gene Expression and Survival Analyses, Intended for Biomedical Researchers Genomic data from The Cancer Genome Atlas (TCGA) project has enabled comprehensive molecular profiling of diverse cancer types. The extensive sample size within TCGA provides an invaluable resource for investigating tumor heterogeneity. Effective exploration of this dataset by researchers and clinicians is essential for discovering novel therapeutic and diagnostic biomarkers. While numerous computational tools have been developed to analyze specific aspects of TCGA data, there remains a need for platforms that facilitate the study of gene expression variability and its association with clinical outcomes across tumors. Here, we introduce the  R2 Platform , an intuitive and interactive web portal designed for in-depth analysis of TCGA gene expression data. The portal leverages TCGA Level 3 RNA-seq and clinical data from 31 cancer types. With its user-f...